from sklearn_benchmarks.report import Reporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = Reporting(config_file_path="config.yml")
reporting.run()
| hour | min | sec | |
|---|---|---|---|
| algo | |||
| KNeighborsClassifier | 0.0 | 14.0 | 5.751719 |
| daal4py_KNeighborsClassifier | 0.0 | 5.0 | 14.647524 |
| KNeighborsClassifier_kd_tree | 0.0 | 7.0 | 1.156226 |
| daal4py_KNeighborsClassifier_kd_tree | 0.0 | 1.0 | 58.342032 |
| KMeans_tall | 0.0 | 1.0 | 46.357864 |
| daal4py_KMeans_tall | 0.0 | 1.0 | 20.086135 |
| KMeans_short | 0.0 | 0.0 | 26.516990 |
| daal4py_KMeans_short | 0.0 | 0.0 | 13.013196 |
| LogisticRegression | 0.0 | 1.0 | 9.498622 |
| daal4py_LogisticRegression | 0.0 | 1.0 | 1.267309 |
| Ridge | 0.0 | 1.0 | 2.979048 |
| daal4py_Ridge | 0.0 | 0.0 | 23.372518 |
| total | 0.0 | 35.0 | 43.088614 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier | fit | 0.143 | 0.006 | 1000000 | 1000000 | 100 | brute | -1 | 1 | NaN | NaN | 0.495 | 0.008 | 0.289 | 0.013 | See |
| 1 | KNeighborsClassifier | predict | 0.184 | 0.013 | 1000000 | 1 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 0.102 | 0.004 | 1.809 | 0.140 | See |
| 2 | KNeighborsClassifier | predict | 30.775 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 1 | 1.0 | 0.0 | 3.842 | 0.023 | 8.010 | 0.047 | See |
| 3 | KNeighborsClassifier | fit | 0.144 | 0.005 | 1000000 | 1000000 | 100 | brute | -1 | 5 | NaN | NaN | 0.487 | 0.004 | 0.295 | 0.010 | See |
| 4 | KNeighborsClassifier | predict | 0.195 | 0.008 | 1000000 | 1 | 100 | brute | -1 | 5 | 1.0 | 0.0 | 0.100 | 0.003 | 1.944 | 0.097 | See |
| 5 | KNeighborsClassifier | predict | 39.682 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 5 | 1.0 | 0.0 | 3.854 | 0.024 | 10.296 | 0.065 | See |
| 6 | KNeighborsClassifier | fit | 0.128 | 0.003 | 1000000 | 1000000 | 100 | brute | -1 | 100 | NaN | NaN | 0.494 | 0.010 | 0.259 | 0.008 | See |
| 7 | KNeighborsClassifier | predict | 0.189 | 0.013 | 1000000 | 1 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 0.101 | 0.002 | 1.870 | 0.141 | See |
| 8 | KNeighborsClassifier | predict | 39.844 | 0.000 | 1000000 | 1000 | 100 | brute | -1 | 100 | 1.0 | 1.0 | 3.917 | 0.014 | 10.173 | 0.037 | See |
| 9 | KNeighborsClassifier | fit | 0.128 | 0.002 | 1000000 | 1000000 | 100 | brute | 1 | 1 | NaN | NaN | 0.499 | 0.015 | 0.256 | 0.008 | See |
| 10 | KNeighborsClassifier | predict | 0.190 | 0.003 | 1000000 | 1 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 0.102 | 0.002 | 1.869 | 0.051 | See |
| 11 | KNeighborsClassifier | predict | 15.592 | 0.023 | 1000000 | 1000 | 100 | brute | 1 | 1 | 1.0 | 0.0 | 3.850 | 0.048 | 4.050 | 0.051 | See |
| 12 | KNeighborsClassifier | fit | 0.129 | 0.003 | 1000000 | 1000000 | 100 | brute | 1 | 5 | NaN | NaN | 0.488 | 0.005 | 0.264 | 0.008 | See |
| 13 | KNeighborsClassifier | predict | 0.202 | 0.005 | 1000000 | 1 | 100 | brute | 1 | 5 | 1.0 | 0.0 | 0.099 | 0.003 | 2.032 | 0.078 | See |
| 14 | KNeighborsClassifier | predict | 25.845 | 0.005 | 1000000 | 1000 | 100 | brute | 1 | 5 | 1.0 | 0.0 | 3.864 | 0.035 | 6.689 | 0.061 | See |
| 15 | KNeighborsClassifier | fit | 0.142 | 0.005 | 1000000 | 1000000 | 100 | brute | 1 | 100 | NaN | NaN | 0.492 | 0.015 | 0.288 | 0.013 | See |
| 16 | KNeighborsClassifier | predict | 0.203 | 0.006 | 1000000 | 1 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 0.101 | 0.003 | 2.007 | 0.089 | See |
| 17 | KNeighborsClassifier | predict | 25.784 | 0.040 | 1000000 | 1000 | 100 | brute | 1 | 100 | 1.0 | 1.0 | 3.917 | 0.023 | 6.583 | 0.040 | See |
| 18 | KNeighborsClassifier | fit | 0.063 | 0.005 | 1000000 | 1000000 | 2 | brute | -1 | 1 | NaN | NaN | 0.107 | 0.004 | 0.592 | 0.050 | See |
| 19 | KNeighborsClassifier | predict | 0.020 | 0.002 | 1000000 | 1 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.004 | 0.000 | 4.700 | 0.508 | See |
| 20 | KNeighborsClassifier | predict | 24.904 | 0.035 | 1000000 | 1000 | 2 | brute | -1 | 1 | 1.0 | 1.0 | 0.833 | 0.071 | 29.908 | 2.545 | See |
| 21 | KNeighborsClassifier | fit | 0.060 | 0.001 | 1000000 | 1000000 | 2 | brute | -1 | 5 | NaN | NaN | 0.106 | 0.004 | 0.564 | 0.022 | See |
| 22 | KNeighborsClassifier | predict | 0.028 | 0.003 | 1000000 | 1 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.005 | 0.000 | 6.105 | 0.696 | See |
| 23 | KNeighborsClassifier | predict | 34.340 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 5 | 1.0 | 1.0 | 0.823 | 0.015 | 41.750 | 0.751 | See |
| 24 | KNeighborsClassifier | fit | 0.060 | 0.002 | 1000000 | 1000000 | 2 | brute | -1 | 100 | NaN | NaN | 0.105 | 0.003 | 0.575 | 0.024 | See |
| 25 | KNeighborsClassifier | predict | 0.028 | 0.001 | 1000000 | 1 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.005 | 0.001 | 5.497 | 0.604 | See |
| 26 | KNeighborsClassifier | predict | 34.189 | 0.000 | 1000000 | 1000 | 2 | brute | -1 | 100 | 1.0 | 1.0 | 0.889 | 0.009 | 38.469 | 0.406 | See |
| 27 | KNeighborsClassifier | fit | 0.060 | 0.003 | 1000000 | 1000000 | 2 | brute | 1 | 1 | NaN | NaN | 0.107 | 0.004 | 0.560 | 0.035 | See |
| 28 | KNeighborsClassifier | predict | 0.015 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.005 | 0.001 | 3.300 | 0.617 | See |
| 29 | KNeighborsClassifier | predict | 10.821 | 0.058 | 1000000 | 1000 | 2 | brute | 1 | 1 | 1.0 | 1.0 | 0.817 | 0.011 | 13.251 | 0.199 | See |
| 30 | KNeighborsClassifier | fit | 0.059 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 5 | NaN | NaN | 0.105 | 0.002 | 0.564 | 0.025 | See |
| 31 | KNeighborsClassifier | predict | 0.022 | 0.000 | 1000000 | 1 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.005 | 0.000 | 4.794 | 0.396 | See |
| 32 | KNeighborsClassifier | predict | 20.452 | 0.040 | 1000000 | 1000 | 2 | brute | 1 | 5 | 1.0 | 1.0 | 0.829 | 0.016 | 24.670 | 0.469 | See |
| 33 | KNeighborsClassifier | fit | 0.059 | 0.002 | 1000000 | 1000000 | 2 | brute | 1 | 100 | NaN | NaN | 0.106 | 0.004 | 0.561 | 0.024 | See |
| 34 | KNeighborsClassifier | predict | 0.022 | 0.001 | 1000000 | 1 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.005 | 0.000 | 4.694 | 0.478 | See |
| 35 | KNeighborsClassifier | predict | 20.424 | 0.065 | 1000000 | 1000 | 2 | brute | 1 | 100 | 1.0 | 1.0 | 0.884 | 0.009 | 23.091 | 0.241 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | brute |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | accuracy_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 3.260 | 0.029 | 1000000 | 1000000 | 10 | kd_tree | -1 | 1 | NaN | NaN | 0.780 | 0.009 | 4.182 | 0.060 | See |
| 1 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 6.927 | 4.104 | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 0.486 | 0.010 | 1000000 | 1000 | 10 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.113 | 0.004 | 4.286 | 0.165 | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 3.252 | 0.048 | 1000000 | 1000000 | 10 | kd_tree | -1 | 5 | NaN | NaN | 1.042 | 0.018 | 3.120 | 0.071 | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 6.108 | 2.652 | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 0.891 | 0.018 | 1000000 | 1000 | 10 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.227 | 0.006 | 3.921 | 0.132 | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 3.198 | 0.034 | 1000000 | 1000000 | 10 | kd_tree | -1 | 100 | NaN | NaN | 0.817 | 0.026 | 3.915 | 0.133 | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.005 | 0.001 | 1000000 | 1 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.001 | 0.000 | 5.333 | 2.037 | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 2.825 | 0.025 | 1000000 | 1000 | 10 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.669 | 0.007 | 4.223 | 0.059 | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 3.240 | 0.016 | 1000000 | 1000000 | 10 | kd_tree | 1 | 1 | NaN | NaN | 0.995 | 0.074 | 3.257 | 0.244 | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 3.156 | 1.386 | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 0.803 | 0.017 | 1000000 | 1000 | 10 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.126 | 0.009 | 6.385 | 0.498 | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 3.239 | 0.039 | 1000000 | 1000000 | 10 | kd_tree | 1 | 5 | NaN | NaN | 0.815 | 0.020 | 3.975 | 0.110 | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.002 | 0.000 | 1000000 | 1 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 2.874 | 1.192 | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1.550 | 0.009 | 1000000 | 1000 | 10 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.223 | 0.008 | 6.954 | 0.254 | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 3.256 | 0.059 | 1000000 | 1000000 | 10 | kd_tree | 1 | 100 | NaN | NaN | 1.000 | 0.034 | 3.257 | 0.126 | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.001 | 1000000 | 1 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.002 | 0.003 | 1.783 | 2.554 | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 5.163 | 0.055 | 1000000 | 1000 | 10 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.700 | 0.016 | 7.372 | 0.182 | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1.315 | 0.014 | 1000000 | 1000000 | 2 | kd_tree | -1 | 1 | NaN | NaN | 0.522 | 0.015 | 2.519 | 0.076 | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 16.274 | 8.127 | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 0.040 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 48.114 | 11.919 | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1.340 | 0.010 | 1000000 | 1000000 | 2 | kd_tree | -1 | 5 | NaN | NaN | 0.502 | 0.010 | 2.670 | 0.055 | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 13.738 | 7.045 | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 0.043 | 0.002 | 1000000 | 1000 | 2 | kd_tree | -1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 34.046 | 7.068 | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1.360 | 0.018 | 1000000 | 1000000 | 2 | kd_tree | -1 | 100 | NaN | NaN | 0.511 | 0.010 | 2.664 | 0.063 | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.003 | 0.000 | 1000000 | 1 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 17.218 | 8.167 | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 0.063 | 0.003 | 1000000 | 1000 | 2 | kd_tree | -1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 8.630 | 0.883 | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1.335 | 0.027 | 1000000 | 1000000 | 2 | kd_tree | 1 | 1 | NaN | NaN | 0.502 | 0.007 | 2.660 | 0.064 | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.000 | 0.000 | 4.776 | 2.443 | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 0.039 | 0.003 | 1000000 | 1000 | 2 | kd_tree | 1 | 1 | 1.0 | 1.0 | 0.001 | 0.000 | 47.136 | 12.201 | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1.328 | 0.019 | 1000000 | 1000000 | 2 | kd_tree | 1 | 5 | NaN | NaN | 0.524 | 0.014 | 2.536 | 0.078 | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.000 | 0.000 | 4.967 | 2.548 | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 0.043 | 0.003 | 1000000 | 1000 | 2 | kd_tree | 1 | 5 | 1.0 | 1.0 | 0.001 | 0.000 | 35.096 | 7.979 | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1.316 | 0.015 | 1000000 | 1000000 | 2 | kd_tree | 1 | 100 | NaN | NaN | 0.516 | 0.012 | 2.552 | 0.068 | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.001 | 0.000 | 1000000 | 1 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.000 | 0.000 | 4.405 | 2.110 | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 0.072 | 0.004 | 1000000 | 1000 | 2 | kd_tree | 1 | 100 | 1.0 | 1.0 | 0.007 | 0.001 | 10.007 | 0.935 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | kd_tree |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 0.647 | 0.015 | 1000000 | 1000000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.319 | 0.008 | 2.028 | 0.070 | See |
| 1 | KMeans_tall | predict | 0.001 | 0.001 | 1000000 | 1 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 3.483 | 4.073 | See |
| 2 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1000 | 2 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.790 | 0.870 | See |
| 3 | KMeans_tall | fit | 0.570 | 0.013 | 1000000 | 1000000 | 2 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.277 | 0.014 | 2.057 | 0.114 | See |
| 4 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.200 | 1.157 | See |
| 5 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 2 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.183 | 1.407 | See |
| 6 | KMeans_tall | fit | 7.300 | 0.082 | 1000000 | 1000000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.893 | 0.027 | 1.875 | 0.025 | See |
| 7 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.924 | 0.966 | See |
| 8 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | k-means++ | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.281 | 0.901 | See |
| 9 | KMeans_tall | fit | 6.541 | 0.024 | 1000000 | 1000000 | 100 | full | random | 30 | 3 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 3.693 | 0.018 | 1.771 | 0.011 | See |
| 10 | KMeans_tall | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.658 | 1.020 | See |
| 11 | KMeans_tall | predict | 0.001 | 0.000 | 1000000 | 1000 | 100 | full | random | 30 | 3 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.159 | 0.940 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 3 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | algorithm | init | max_iter | n_clusters | n_init | tol | n_iter_sklearn | adjusted_rand_score_sklearn | n_iter_daal4py | adjusted_rand_score_daal4py | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 0.391 | 0.021 | 10000 | 10000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.149 | 0.009 | 2.626 | 0.213 | See |
| 1 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.138 | 1.563 | See |
| 2 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.260 | 0.293 | See |
| 3 | KMeans_short | fit | 0.144 | 0.003 | 10000 | 10000 | 2 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 30.0 | NaN | 0.071 | 0.002 | 2.036 | 0.068 | See |
| 4 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.843 | 0.989 | See |
| 5 | KMeans_short | predict | 0.001 | 0.000 | 10000 | 1000 | 2 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.001 | 0.000 | 1.327 | 0.337 | See |
| 6 | KMeans_short | fit | 1.265 | 0.035 | 10000 | 10000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | 22.0 | NaN | 22.0 | NaN | 0.599 | 0.055 | 2.112 | 0.202 | See |
| 7 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 2.052 | 1.016 | See |
| 8 | KMeans_short | predict | 0.007 | 0.004 | 10000 | 1000 | 100 | full | k-means++ | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 4.085 | 2.834 | See |
| 9 | KMeans_short | fit | 0.406 | 0.062 | 10000 | 10000 | 100 | full | random | 30 | 300 | 1 | 0.0 | 30.0 | NaN | 20.0 | NaN | 0.314 | 0.036 | 1.293 | 0.247 | See |
| 10 | KMeans_short | predict | 0.000 | 0.000 | 10000 | 1 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.000 | 0.000 | 1.919 | 0.865 | See |
| 11 | KMeans_short | predict | 0.004 | 0.003 | 10000 | 1000 | 100 | full | random | 30 | 300 | 1 | 0.0 | NaN | 1.0 | NaN | 1.0 | 0.002 | 0.000 | 2.444 | 1.508 | See |
Shared hyperparameters:
| value | |
|---|---|
| algorithm | full |
| n_clusters | 300 |
| max_iter | 30 |
| n_init | 1 |
| tol | 0.0 |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 15.627 | 0.008 | 1000000 | 1000000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [20] | 15.652 | 0.023 | 0.998 | 0.002 | See |
| 1 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.377 | 0.380 | See |
| 2 | LogisticRegression | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.000 | 0.000 | 0.937 | 0.343 | See |
| 3 | LogisticRegression | fit | 1.209 | 0.032 | 1000 | 1000 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | [26] | 1.185 | 0.027 | 1.020 | 0.036 | See |
| 4 | LogisticRegression | predict | 0.000 | 0.000 | 1000 | 1 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.001 | 0.000 | 0.127 | 0.079 | See |
| 5 | LogisticRegression | predict | 0.002 | 0.000 | 1000 | 100 | 10000 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0 | 0 | False | NaN | 0.005 | 0.002 | 0.440 | 0.182 | See |
Shared hyperparameters:
| value | |
|---|---|
| penalty | l2 |
| dual | False |
| tol | 0.0001 |
| C | 1.0 |
| fit_intercept | True |
| intercept_scaling | 1 |
| class_weight | NaN |
| random_state | NaN |
| solver | lbfgs |
| max_iter | 100 |
| multi_class | auto |
| verbose | 0 |
| warm_start | False |
| n_jobs | NaN |
| l1_ratio | NaN |
| estimator | function | mean_sklearn | stdev_sklearn | n_samples_train | n_samples | n_features | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | n_iter | mean_daal4py | stdev_daal4py | speedup | stdev_speedup | profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 2.741 | 0.037 | 100000 | 100000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 1.582 | 0.018 | 1.733 | 0.031 | See |
| 1 | Ridge | predict | 0.000 | 0.000 | 100000 | 1 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.599 | 0.516 | See |
| 2 | Ridge | predict | 0.001 | 0.000 | 100000 | 1000 | 1000 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.001 | 0.000 | 0.681 | 0.226 | See |
| 3 | Ridge | fit | 1.426 | 0.036 | 1000000 | 1000000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.338 | 0.006 | 4.225 | 0.130 | See |
| 4 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.434 | 0.422 | See |
| 5 | Ridge | predict | 0.000 | 0.000 | 1000000 | 1000 | 100 | 1.0 | True | True | NaN | False | NaN | auto | 0.001 | NaN | 0.000 | 0.000 | 0.597 | 0.338 | See |
Shared hyperparameters:
| value | |
|---|---|
| alpha | 1.0 |
| fit_intercept | True |
| normalize | False |
| copy_X | True |
| max_iter | NaN |
| tol | 0.001 |
| solver | auto |
| random_state | NaN |
{
"system_info": {
"python": "3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27) [GCC 9.3.0]",
"executable": "/usr/share/miniconda/envs/sklbench/bin/python",
"machine": "Linux-5.4.0-1046-azure-x86_64-with-glibc2.10"
},
"dependencies_info": {
"pip": "21.1",
"setuptools": "49.6.0.post20210108",
"sklearn": "0.24.1",
"numpy": "1.20.2",
"scipy": "1.6.2",
"Cython": null,
"pandas": "1.2.4",
"matplotlib": null,
"joblib": "1.0.1",
"threadpoolctl": "2.1.0"
},
"threadpool_info": [
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libopenblasp-r0.3.12.so",
"prefix": "libopenblas",
"user_api": "blas",
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"version": "0.3.12",
"num_threads": 2,
"threading_layer": "pthreads"
},
{
"filepath": "/usr/share/miniconda/envs/sklbench/lib/libgomp.so.1.0.0",
"prefix": "libgomp",
"user_api": "openmp",
"internal_api": "openmp",
"version": null,
"num_threads": 2
}
],
"cpu_count": 2
}